Techniques for collecting, managing and providing real-time or near real-time relevant information have been enhanced through the use of the Internet and online research and information collection tools. One such set of tools is known as web analytics. Web analytics focuses on a company's own website for collection of online information, particularly traffic data. Web analytics are limited in that they only consider a subset of the relevant online universe, specifically the behavior of users of a given website.
Other analytics tools try to learn and predict the exposure and reach of advertisements displayed on web-sites including the social media websites. These tools gather campaign data, such as statistics related to the reach and exposure of the advertisements. The campaign data may include the number of impressions, URLs of web-pages displaying the advertisements, geographical locations of users that watched the advertisements, click-through rate of advertisements, the period of time that each viewer watched the advertisements, and so on.
Currently, every ad-serving company as well as each social media website independently gathers its own campaign data and analytics with regard to the exposure and reach of advertisements. However, campaign managers who like to have better understanding about the reach and whether their budget was well spent have limited tools by which to do so. As a result, campaign managers cannot efficiently analyze and understand the performance of an advertisement campaign.
Specifically, the information gathered by a single ad-serving company or a social website per campaign may include trillions of records. Multiplying these by different companies serving the same campaigns makes it almost impossible for campaign managers to analyze the gathered information using existing tools. Furthermore, in addition to the volume of the gathered information, campaign data gathered by such ad-serving companies come in many different forms and formats. For example, a field name of the same measure (e.g., click-through) may be expressed differently by different companies or in different campaigns. The file formats may be different and may include file formats such as Excel, XML, plain text, and the like. This further increases the complexity of the campaign analysis.
It should be noted that failing to efficiently and accurately analyze the performance of an advertising campaign results in revenue losses for businesses, as their advertising budget is not being efficiently spent.
It would therefore be advantageous to provide a solution that would overcome the deficiencies noted above.